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Influence of Texting on Driver Glance Patterns and Vehicular Lane Position on Horizontal Curves Presented by: Makenzie Ellett Research Assistant Oregon State University School of Civil and Construction Engineering March 20 th , 2015 Forsyth

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Page 1: Ellett Presentation - Final

Influence of Texting on Driver Glance Patterns and Vehicular Lane Position on

Horizontal Curves

Presented by:

Makenzie EllettResearch Assistant Oregon State UniversitySchool of Civil and Construction Engineering

March 20th, 2015

Forsyth

Page 2: Ellett Presentation - Final

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Background – Cell Phone Use

• The first cell phone, 1983• 1985: 340,000 subscribers• 2000: 100 million subscribers• 94% of people in the US aged 16+

owned a mobile device in 2013

• The first text message, 1992• “Merry Christmas” • 1997, USA: 40,000 text messages/day• 2012, USA: 6 billion text

messages/day • Most popular cell phone feature

(CTIA, 2013)

Number of Cell Phone Subscribers in the United States

1980 1985 1990 1995 2000 2005 2010 20150

50100150200250300350

Year

Num

ber

of S

ubsc

ribe

rs

(in

mill

ions

)

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

01234567

Year

Num

ber

of T

ext

Mes

sage

s (b

il-lio

ns)

Number of Text Messages Sent Per Day in the United States

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Background – Distracted Driving

Distraction Types (NHTSA)

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Background – Safety of Texting and Driving

• Risk of crash increases by 23.24 times (Olson et al., 2009) • Conversing on a hand-held mobile

phone increases crash risk 1.04 times• Texting is the most dangerous activity

while driving

• National Survey on Distracted Driving Attitudes and Behaviors• 32.9% believe there is no difference in

their driving• 92.2% feel at least “somewhat

uncomfortable” when riding with a driver who texts

Percentage of Population Observed Manipulating Hand-

Held Devices (NOPUS)

Driver Type 2010 2011

All Drivers 0.90% 1.30%

Age 25-69 0.80% 1.10%

Age 16-24 1.50% 3.70%

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Background – Legality of Texting while Driving

Laws Regarding Texting While Driving By State

LEGENDNo Ban

Total Ban (Primary Law)Total Ban (Secondary

Law)Partial Ban (School Bus & Novice Drivers)Partial Ban (Novice Drivers

Only)

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Literature Review – Glance Patterns

• The longer a driver’s eyes are away from the roadway, the greater the odds ratios of a crash incident

• For an “incident” to occur, driver glances of 1.1 sec. were observed (Klauer et al., 2006)

• Texting defined as a “complex, tertiary task” (Olson et al., 2009)

Odds Ratios Associated with Eyes Off of the Forward Roadway (Klauer et al., 2006)

Total Eyes off Forward Roadway Odds Ratios

Lower Control Limit Upper Control Limit

Time (seconds) (LCL) (UCL)

t ≤ 0.5 1.13 0.67 1.92

0.5 < t ≤ 1.0 1.12 0.79 1.59

1.0 < t ≤ 1.5 1.14 0.79 1.65

1.5 < t ≤ 2.0 1.41 0.98 2.04

t > 2.0 2.27 1.79 2.86

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Literature Review – Lateral Position• As distraction levels increase, the vehicle’s standard deviation of

lateral position (SDLP) also increases

• 70% increase in lane position variability compared to baseline (Hosking et al., 2006)

• Lane excursions increase when texting (Reed et al., 2008)• Reading: 8 to 18• Writing: 4 to 42

Measuring Standard Deviation of Lateral Position (Verster et al., 2011)

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Methodology - Research Hypotheses

H0: There is no difference in the duration of driver fixations on a mobile phone while completing a text messaging task between four horizontal curves.

? ? ?Curve 1

Curve 2

Curve 3

Curve 4

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Methodology - Research Hypotheses

H0: There is no difference in the lateral position of a vehicle between baseline driving and driving while completing a text messaging task between four horizontal curves.

? ? ?Curve 1

Curve 2

Curve 3

Curve 4

(Larmoyeux & Bone)

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Methodology - Research Hypotheses

H0: There is no difference in the lateral position of a vehicle before, during, or after the text messaging task between four horizontal curves.

? ? ?Curve 1

Curve 2

Curve 3

Curve 4

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Methodology – Dependent Variables

• Glance frequency towards mobile phone

• Duration of glances towards mobile phone

• Percentage of time on curve subject’s eyes are on the mobile phone

• SDLP of vehicle throughout curve

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Methodology - OSU Driving Simulator

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Methodology - OSU Eye Tracker

Head Mounted Goggles Data Acquisition Unit

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Methodology – Test Track

(Not to Scale)

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Methodology – Scenario

Example of Billboard Image

CURVE IMAGE

1 Cow

2 Cat

3 Eagle

4 Dog

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Methodology – Participants

• Data obtained from Joshua Swake, MS 13’ Thesis• Texting while driving was used as a distractor for the original study• Original research studied driver behavior in work zones

• Original Study: 36 participants• Current Study: 18 participants

• Control Group: 4 subjects (did not text)• Treatment Group: 14 subjects (responded to texting cues)

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Results - Data Collection

Result Data Collection Method Reduction of Data

Driver Glance Patterns

Mobile Eye XG Videos

Researcher Observation

Lateral Position of Vehicle

OSU Driving Simulator CSV Files

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Results - Analysis

• Paired T-test• R-studio• Adjusted for multiple comparisons with

the Benjamini and Yekutieli adjustment• Statistically significant p-values < 0.05• 95% confidence intervals

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Results – Average Duration of Driver Fixations

Average duration of driver fixations

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Results – Average Duration of Driver Fixations

Average duration of driver fixations

Average Duration of Driver Fixations (sec)Curve

Paired T-test

Curve 1 Curve 2 Curve 3 Curve 4 P-value Significant

1.078 1.091 1.090 1.146

1 v 2 0.7311 No

1 v 3 0.6817 No

1 v 4 0.8329 No

2 v 3 0.9922 No

2 v 4 0.5374 No

3 v 4 0.3525 No

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Results – Maximum Duration of Driver Fixations

Maximum duration of driver fixations

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Results – Maximum Duration of Driver Fixations

Statistical summary comparing maximum duration of fixations between curves

Maximum Duration of Driver Fixations (sec)Curve

Paired T-test

Curve 1 Curve 2 Curve 3 Curve 4 P-value Significant

4.04 2.54 2.61 2.87

1 v 2 0.1953 No

1 v 3 0.2701 No

1 v 4 0.1983 No

2 v 3 0.5397 No

2 v 4 0.4081 No

3 v 4 0.7664 No

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Results – Percentage of Time with Eyes Off Roadway

Percentage of time with eyes off roadway

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Results – Average Percentage of Time with Eyes Off Roadway

Statistical summary of average percentage of time with eyes off roadway

Average Percentage of Eyes off Forward RoadwayCurve

Paired T-test

Curve 1 Curve 2 Curve 3 Curve 4 P-value Significant

30.2 20.1 27 24.7

1 v 2 0.06212 Suggestive

1 v 3 0.5885 No

1 v 4 0.2548 No

2 v 3 0.06371 Suggestive

2 v 4 0.05607 Suggestive

3 v 4 0.5473 No

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Results – Average Overall SDLP

Overall SDLP for control condition

Overall SDLP for treatment condition

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Results – Average Overall SDLP

Average overall SDLP for control and treatment conditions

Curve 1 Curve 2 Curve 3 Curve 40.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

2.00

ControlTreatment

SDLP

(ft

)

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Results – Average Overall SDLP

Statistical summary of average overall SDLP for control condition

Average SDLP of Control ConditionCurve

Paired T-test

Curve 1 Curve 2 Curve 3 Curve 4 P-value Significant

1 1.19 1.06 1.05

1 v 2 0.26 No

1 v 3 0.60 No

1 v 4 0.12 No

2 v 3 0.49 No

2 v 4 0.36 No

3 v 4 0.94 No

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Results – Average Overall SDLP

Statistical summary of average overall SDLP for treatment condition

Average SDLP of Treatment ConditionCurve

Paired T-test

Curve 1 Curve 2 Curve 3 Curve 4 P-value Significant

1.77 1.29 1.25 1.26

1 v 2 0.10 No

1 v 3 0.16 No

1 v 4 0.13 No

2 v 3 0.80 No

2 v 4 0.78 No

3 v 4 0.94 No

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Results – Average Overall SDLP Comparison

255 260 265 270 275 280 285 290 2950

5

10

15

20

25Control Subject - Curve 1

Video Time (s)

Lane

Pos

itio

n (f

t)

230 235 240 245 250 255 260 2650

5

10

15

20

25

Treatment Subject - Curve 1

Video Time (s)

Lane

Pos

itio

n (f

t)Comparison of control and treatment subjects’ SDLP

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Results – Average Interval SDLP

SDLP for before interval SDLP for during interval

SDLP for after interval

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Results – Average Interval SDLP

Average overall SDLP for control and treatment conditions

1 2 3 40.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

Before

During

After

Curve

SDLP

(ft

)

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Results – Average Interval SDLP

Average overall SDLP for control and treatment conditions

Statistical summary of average SDLP for before interval

Average SDLP of before PeriodCurve

Paired T-test

Curve 1 Curve 2 Curve 3 Curve 4 P-value Significant

0.6880 0.5473 0.5652 0.6646

1 v 2 0.1678 No

1 v 3 0.2738 No

1 v 4 0.7468 No

2 v 3 0.9487 No

2 v 4 0.2346 No

3 v 4 0.1675 No

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Results – Average Interval SDLP

Statistical summary of average SDLP for during interval

Average SDLP of during PeriodCurve

Paired T-test

Curve 1 Curve 2 Curve 3 Curve 4 P-value Significant

1.1948 1.0280 1.1671 1.0826

1 v 2 0.5976 No

1 v 3 0.7777 No

1 v 4 0.5857 No

2 v 3 0.3269 No

2 v 4 0.7846 No

3 v 4 0.6845 No

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Results – Average Interval SDLP

Statistical summary of average SDLP for after interval

Average SDLP of after PeriodCurve

Paired T-test

Curve 1 Curve 2 Curve 3 Curve 4 P-value Significant

1.0918 0.9341 0.8377 0.8057

1 v 2 0.7251 No

1 v 3 0.6745 No

1 v 4 0.4962 No

2 v 3 0.6771 No

2 v 4 0.2655 No

3 v 4 0.8039 No

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Conclusions – Duration and Frequency of Fixations

H0: There is no difference in the duration of driver fixations on a mobile phone while completing a text messaging task between four horizontal curves.

H0 is not rejected

• No statistically significant differences were found between the fixation durations

• No statistically significant difference was found between the maximum fixation durations

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Conclusions –SDLP of Treatment and Control Groups

H0: There is no difference in the lateral position of a vehicle between baseline driving and driving while completing a text messaging task between four horizontal curves.

H0 is not rejected

• No statistical difference was found in the average SDLP of the treatment group

• No statistical difference was found in the average SDLP of the control group• Treatment group exhibited increased SDLP compared to control group on

all four curves

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Conclusions – SDLP of Before, During, & After Intervals

H0: There is no difference in the lateral position of the vehicle before, during, or after the text messaging task between four horizontal curves.

H0 is not rejected

• No statistically significant difference was found in the average SDLP of the before intervals

• No statistically significant difference was found in the average SDLP of the during intervals

• No statistically significant difference was found in the average SDLP of the after intervals

• Average SDLP was least for before interval on all four curves• Average SDLP was greatest for during interval on all four curves• Average SDLP was noticeably increased during after interval, compared to before

interval

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• A larger, more diverse sample size could result in more specific conclusions relating the effects of age, gender, and driving experience

• A larger sample size could result in statistical conclusions being drawn between the control and treatment groups

• Analysis on the addition of ambient traffic

• Varying the text messaging cues by category, complexity, or prompt-type to see their effects on driver behavior

• Direct comparison of SDLP and glance patterns of texting on horizontal curves and tangent sections

Future Work

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• Dr. David Hurwitz

• Justin Neill

• Joshua Swake

• OSU Transportation Department

• OSU Honors College

Acknowledgements

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QUESTIONS?